Optimum (Wiener sense) filters for suppression of noise in multiple time series are computed by a new method due to E. A. Robinson. Filters for prediction error and interpolation error have been used to detect P‐wave signals from three teleseismic events. These filters facilitate detection of signals in noise with low signal‐to‐noise ratios. The instrumentation consists of short‐period Benioff seismometers, both three‐component stations and surface arrays of verticals. It was found that microseismic noise in the pass band of these instruments is more accurately termed “Brownian motion of a surface” than “random waveforms with characteristic direction(s) of propagation.” Thus, single time‐series filters work almost as well as multiple time‐series matrix filters. Prediction‐error filters gave results substantially more satisfactory than simple band‐pass filters.
Inferring pairwise regulatory relationships from multiple time series datasets